1,721,209 research outputs found
Data: A Novel ELSA Model for Flash Evaporation
No full textOpenFOAM Case Files for "A Novel ELSA Model for Flash Evaporation"
This dataset contains the OpenFOAM case files to generate the published data in:
J. W. Gärtner and A. Kronenburg, "A Novel ELSA Model for Flash Evaporation", International Journal of Multiphase Flow, vol. 174, 2024, doi: 10.1016/j.ijmultiphaseflow.2024.104784
Content
This dataset contains three files:
Codes.tar.gz
Python library to read in sampled line data of OpenFOAM. Required for the jupyter-notebooks in the LN2-2D-RANS and Lebas-TestCases archives.
LN2-2D-RANS.tar.gz
This tar archive contains all OpenFOAM case files of the LN2 cases that are presented in the publication. Further, the jupyter-notebook files to generate the plots of the publication are included.
Lebas-TestCases.tar.gz
This tar archive contains the OpenFOAM cases for the standard ELSA model validation. Further, the jupyter-notebook files to generate the plots of the publication are included.
Requirements
To reproduce the data, OpenFOAM v2012 with the compressiblePhaseChangeFoam solver has to be installed. The compressiblePhaseChangeFoam solver is not a standard OpenFOAM solver and can be accessed on DaRUS at this location:
Compressible Two-Phase One-Fluid Solver
Note that the dataset is restricted, and access has to be requested!
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Replication Data for: Modeling dense droplet spray combustion with multiple-mapping conditioning
No full textModeling dense droplet spray combustion with multiple-mapping conditioning
This data set contains the OpenFOAM case files required for reproducing the results published in:
Jan Wilhelm Gärtner, Ka Ho Lam, Andreas Kronenburg,
Modeling dense droplet spray combustion with multiple-mapping conditioning,
Proceedings of the Combustion Institute,
Volume 41, 2025, 105895, doi: 10.1016/j.proci.2025.105895.
The case files are separated in two tar archives:
DNS: Contains all DNS cases separated in LtoD-5 and LtoD-10 setup
LES: Contains all LES cases separated in LtoD-5 and LtoD-10 setups
The LtoD-5 setup corresponds to the dense case and the LtoD-10 setup to the dilute spray case.
Plot Results
To generate the plots of the paper, the provided Jupyter notebook files may be used. These Jupyter notebook files require two additional Python libraries
OpenFOAM Reader
mmcFoam python library for post-processing
The OpenFOAM Reader is open-source and publicly available on GitHub. The mmcFoam Python library is part of the mmcFoam solver, which is open-source upon registration. If you wish to use mmcFoam, please contact:
Prof. Andreas Kronenburg: [email protected]
Prof. Matthew Cleary: [email protected]<br
Jan-Wilhelm Beck, Aliter loqueris, aliter vivis. Senecas philosophischer Anspruch und seine biographische Realität, 2010
No full textRochette Bruno. Jan-Wilhelm Beck, Aliter loqueris, aliter vivis. Senecas philosophischer Anspruch und seine biographische Realität, 2010. In: L'antiquité classique, Tome 80, 2011. p. 315
Jan-Wilhelm Beck, Aliter loqueris, aliter vivis. Senecas philosophischer Anspruch und seine biographische Realität, 2010
No full textRochette Bruno. Jan-Wilhelm Beck, Aliter loqueris, aliter vivis. Senecas philosophischer Anspruch und seine biographische Realität, 2010. In: L'antiquité classique, Tome 80, 2011. p. 315
Jan-Wilhelm Beck, Terentianus Maurus. De Syllabis. Herausgegeben, übersetzt und erläutert
No full textDesy Philippe. Jan-Wilhelm Beck, Terentianus Maurus. De Syllabis. Herausgegeben, übersetzt und erläutert. In: L'antiquité classique, Tome 64, 1995. pp. 336-337
Jan-Wilhelm Beck, Terentianus Maurus. De Syllabis. Herausgegeben, übersetzt und erläutert
No full textDesy Philippe. Jan-Wilhelm Beck, Terentianus Maurus. De Syllabis. Herausgegeben, übersetzt und erläutert. In: L'antiquité classique, Tome 64, 1995. pp. 336-337
Replication Data for: mmcDNSFoam v2406
No full textValidation Data for mmcDNSFoam
This data set contains the DNS and LES cases for the double shear layer setup used to validate the mmcDNSFoam solver of the mmcFoam v2406 version.
Requirements
To run the simulations, you need to download and compile the mmcFoam software based on OpenFOAM v2406. This software is open-source upon registration. If you wish to use mmcFoam please contact:
Prof. Andreas Kronenburg: [email protected]
Prof. Matthew Cleary: [email protected]
Please note that you have to merge in the OpenFOAM patch of commit 52b530fb before compiling mmcFoam-v2406. See also, issue #3277.
Additional Libraries
This data set also includes following libraries:
ofReader: Python tools to post-process and read OpenFOAM files
sigmaTurbulenceModel: Implementation of the sigma turbulence model for OpenFOAM v2312 and OpenFOAM v2412, which is compatible with GCC 11.3 compiler.
</ul
Replication Data for: mmcFoam-v2306
No full textData for mmcFoam v2306 Test Runs
This data set contains different cases for validation of the mmcFoam-v2306 version. While tested for mmcFoam-2306 and OpenFOAM-v2306 they serve as a test basis for future code development and validation.
Requirements
To run the simulations, you need to download and compile the mmcFoam software based on OpenFOAM v2306. This software is open-source upon registration. If you wish to use mmcFoam please contact:
Prof. Andreas Kronenburg: [email protected]
Prof. Matthew Cleary: [email protected]
Content
mmcFoam-particleMatchingAlgorithm-greedySearch:
Compares the particle mixing distances in reference and physical
space for two different particle pairing algorithms.
samplingInletData:
Tool to sample inlet data (or any data)
Required to regenerate the inlet data for the sandiaFlame
sandiaFlame:
Setup for the Sandia sooting flame case. However, the inlet data
has to be regenerated as it is too large for this repository > 80GB
--> See samplingInletData tool
shearLayerCase:
Provides setup for the double shear layer with mmcFoam 5.x and
mmcFoam v2212. Different decompositions or particle pairing methods
can be tested.
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Replication Data for: mmcDropletSprayFoam v2406
No full textValidation Data for mmcDropletSprayFoam
This data set contains the DNS and LES cases for the double shear layer setup used to validate the mmcDropletSprayFoam solver of the mmcFoam v2406 version.
Requirements
To run the simulations you need to download and compile the mmcFoam software based on OpenFOAM v2312. This software is open-source upon registration. If you wish to use mmcFoam please contact:
Prof. Andreas Kronenburg: [email protected]
Prof. Matthew Cleary: [email protected]
Additional Libraries
This data set also includes following libraries:
ofReader: Python tools to post-process and read OpenFOAM files
sigmaTurbulenceModel: Implementation of the sigma turbulence model for OpenFOAM v2312 and OpenFOAM v2412, which is compatible with GCC 11.3 compiler.
</ul
Source Code: A Chemistry Load Balancing Model for OpenFOAM
No full textEfficient simulation tools are crucial for studying complex systems such as
reacting flows where computational costs of computing chemical reaction rates can vastly exceed the costs for the integration of the convective and diffusive transport terms. Load imbalance in parallel computing poses a significant challenge for massively parallel reacting flow simulations. In response, a novel load balancing library has been developed to enhance OpenFOAM’s solver performance in parallel environments. This library seamlessly integrates with OpenFOAM, offering ease of use and applicability to any OpenFOAM reacting solver incorporating finite-chemistry. In addition, it supports the standard and the dynamic adaptive chemistry model (TDAC) of OpenFOAM. The newly developed load-balanced standard and TDAC models address significant load imbalances by exchanging information between processes via MPI calls and tracking ODE solution times on a cell level. The TDAC model introduces dual tables on each core and enables immediate addition of computed solutions, enhancing computational efficiency. Validation on various test cases, including simulations on the HLRS Hawk supercomputer up to 8000 cores, confirm identical results compared to the original unbalanced models, with notable speed-up factors of up to 6 for the standard and 5 for the TDAC model. Despite non-linear scaling at lower cell count per processor, load-balanced models consistently outperform unbalanced counterparts, making them the preferred choice for reacting flow simulations in OpenFOAM.
See more information about the usage of this library in the README.</p
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